The most important AI consulting skill for 2026: Understanding AI Debt

This. All of it. Now, I know some people think that I am too focused on monetization, cost, and value. That's their opinion, and they're welcome to it. My perspective is pretty straightforward: As soon as you monetize, you "get real" about what you consume and provide. Until you do, you're likely to delude yourself. The world is changing, and your operating model may be the next casualty. Whether you're an end-user or technology provider, we need to think beyond initial costs. We need to improve our ability to manage the full lifecycle costs. Doing this ensures that you can demonstrate your ability to deliver value and do it sustainably.

𝗟𝗟𝗠𝘀 𝘀𝗼𝘂𝗻𝗱 𝗯𝗿𝗶𝗹𝗹𝗶𝗮𝗻𝘁… 𝗯𝘂𝘁 𝗱𝗼 𝘁𝗵𝗲𝘆 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗿𝗲𝗺𝗲𝗺𝗯𝗲𝗿 𝗮𝗻𝘆𝘁𝗵𝗶𝗻𝗴? Every time we chat with a Large Language Model (LLM), it forgets the past. Unless we provide the history again, it treats each conversation as completely new. This makes us wonder: 🔹If they can’t remember, can we really call them intelligent? The truth is, today’s LLMs are not “thinking machines.” They are advanced pattern predictors — generating answers based on training data, not true memory or understanding. That’s why the future focus is on: 🔹𝘼𝙙𝙙𝙞𝙣𝙜 𝙢𝙚𝙢𝙤𝙧𝙮 so LLMs can recall past interactions. 🔹𝘽𝙪𝙞𝙡𝙙𝙞𝙣𝙜 𝘼𝙄 𝙖𝙜𝙚𝙣𝙩𝙨 that combine reasoning, tools, and memory to act smarter. Until then, LLMs are impressive, but not truly intelligent — more like excellent imitators. #AI #LLM #ArtificialIntelligence #MachineLearning #FutureOfAI #GenerativeAI #Innovation

"The overall average score for the group was poor. AI optimists will intone their mantra that these models will only get better. Realists will say that AI, like Excel, can only boost productivity and that’s enough to make a difference." More, bigger and faster is not the same as better, as we knew. Though it may contribute to either better and worse, as we know.

💥 Are we in the 'Second Half' of AI research and development? I strongly recommend any AI practitioner read the following article. The author argues that algorithms: PPO, RL, Transformers, and so forth, were the first half of the AI game, but now the direction must change. Benchmarks are slowly becoming obsolete. Utility is what matters. Can an LLM complete useful, actionable tasks? Soon, benchmarks won't matter. Impact will. Great stuff herein: https://lnkd.in/e8xXVsj7

Massachusetts Institute of Technology’s new report shocks the AI world: 95% of generative AI pilots deliver no ROI, highlighting what it calls the “GenAI Divide.” Yet, the real problem isn’t AI’s power but its unchecked confidence. PromptQL offers a radical rethink—an AI that is transparent about uncertainty, flags its limits, and learns from corrections. PromptQL is winning trust in the toughest enterprise environments by embracing humility over hubris. Amid the hype and skepticism, it’s proof that scalable, trustworthy AI isn’t a fantasy—it’s already here, quietly reshaping the future. Full story -- https://lnkd.in/dAW8VB56

We’ve been told that #AI will make us smarter, faster, and more productive. But the more insidious danger lies in its very competence. AI doesn’t just scale creativity or efficiency. It scales mediocrity. At first glance, competence looks harmless: clean prose, tidy logic, polished delivery. However, when everything appears credible, the signal that indicates what truly matters becomes weakened. The result is a culture where attention is drawn to what is easiest to produce and spreads frictionlessly. Distinction doesn’t merely compete; it suffocates. https://lnkd.in/ekT3KqZt

Many organizations overlook the value of Humans in the Loop (HITL), thinking it’s costly, slow, or unnecessary. The truth is, human oversight prevents costly AI mistakes, ensures better decision-making, and keeps systems aligned with real-world context. You don’t need endless in-house expertise, HITL can be designed and scaled with the right approach or partner. When done right, it’s not an extra step, but a key factor in building smarter, more reliable, and responsible AI solutions. Learn more in our blog: https://lnkd.in/gk6dVXVY #DataQuality #AITrends #HITL #DataDrivenDecisions #AI

Thanks Dmitriy Bechutskiy for the interesting post))) Most AI projects don't fail because the tech is wrong. They fail because the strategy is. A recent PwC study found that while 60% of tech leaders are confident they can scale AI, only 44% are confident they can deliver tangible results. This "confidence gap" is where ROI goes to die. We see three common mistakes that turn promising AI initiatives into expensive science projects. Avoid these pitfalls to ensure your investment in innovation actually pays off. Which of these challenges have you run into? #AI  #ArtificialIntelligence #TechStrategy  #ROI  #AIForBusiness #AIFuture #AIInnovation #AIMarketing 

Beyond simple inspection, harness the power of image analysis to unlock hidden data, optimize processes, and drive innovation with newfound intelligence.#imageanalysis #optimization #industrialautomation #AI #logistics #innovation #bigdata #processoptimization #visualintelligence - https://lnkd.in/dtKC8hMi

So you may have heard about #DigitalTax, but what about #VerificationTax? I came across this term recently and found it intriguing in the context of all things #AI. Here's what I could make out.. #VerificationTax is the additional time and effort humans must spend to double check the output of #GenerativeAI reports, because of it's tendency to be so - #ConfidentlyWrong. The #MITstudy views, Verification Tax as an impediments towards AI's wide scale adoption. .. while there is hope that AI will evolve and become smarter as we go along, but for now it seems this issue remains. Read more about the MIT Study here: https://lnkd.in/gfPXWt8c Hope you find it of interest. Happy to hear views.. #Disruption I #Artificialintelligence l #LeadershipImperatives